Use of the extended Kalman filter for state dependent drift estimation in weakly nonlinear sensors

A number of mechanisms are responsible for the generation of reversible or irreversible drift in the response of a sensor. In this letter, we discuss three approaches for the identification of reversible state dependent drift in sensors through the use of the Extended Kalman Filter. We compare their performance by simulation and demonstrate their validity by estimating the drift of an accelerometer, modeled as a weakly nonlinear system.